Datasets › DreamBooth

DreamBooth

Introduced by Nataniel Ruiz et al. in DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation25 Aug 2022 archive 2025-07-28

The DreamBooth dataset is a collection of images used for fine-tuning text-to-image diffusion models for subject-driven generation¹. Here are some key details about the dataset:

  • The dataset includes 30 subjects from 15 different classes¹.
  • Among these subjects, 9 are live subjects (such as dogs and cats) and 21 are objects¹.
  • The dataset contains a variable number of images per subject, typically between 4 to 6 images¹.
  • Images of the subjects are usually captured in different conditions, environments, and under different angles¹.
  • The dataset also includes a file prompts_and_classes.txt which contains all of the prompts used in the paper for live subjects and objects, as well as the class name used for the subjects¹.
  • The images have either been captured by the paper authors or sourced from www.unsplash.com¹.
  • The references_and_licenses.txt file contains a list of all the reference links to the images in www.unsplash.com, along with the attribution to the photographer and the license of the image¹.

This dataset is part of the official repository for the Google paper "DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation"¹. If you use this work, please cite the paper¹. Please note that this is not an officially supported Google product¹.

(1) GitHub - google/dreambooth. https://github.com/google/dreambooth. (2) DreamBooth - Hugging Face. https://huggingface.co/docs/diffusers/training/dreambooth. (3) google/dreambooth · Datasets at Hugging Face. https://huggingface.co/datasets/google/dreambooth. (4) dreambooth: Mirror of https://huggingface.co/datasets/google .... https://gitee.com/hf-datasets/dreambooth. (5) undefined. https://github.com/huggingface/diffusers. (6) undefined. https://huggingface.co/datasets/google.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Personalized Image Generation DreamBooth DreamBooth LoRA SDXL v1.0 Overall (CP * PF) 0.517 DreamBooth: Fine Tuning Text-to-Image Diffusion Models... PaddlePaddle/PaddleNLP +11 7 Compare

Papers archive 2025-07-28

5 shown of 5 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 523. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Generative Multimodal Models are In-Context Learners 1 1 20 Dec 2023 ran 3 of 4 samples (1 unverified)
IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models 4 2 13 Aug 2023 ran 3 of 8 samples (5 unverified)
BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing 1 1 24 May 2023 not harvested
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation 12 2 25 Aug 2022 ran 10 of 12 samples (2 unverified; 8 pointer-only for licence)
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion 9 1 2 Aug 2022 ran 10 of 13 samples (3 unverified; 1 pointer-only for licence)

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • DreamBooth

1 variant name, as the archive lists them.

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